Global disparities in patients with multiple myeloma: a rapid evidence assessment

There are disparities in outcomes for patients with multiple myeloma (MM). We evaluated the influence of sociodemographic factors on global disparities in outcomes for patients with MM. This rapid evidence assessment (PROSPERO, CRD42021248461) followed PRISMA-P guidelines and used the PICOS framework. PubMed and Embase® were searched for articles in English from 2011 to 2021. The title, abstract, and full text of articles were screened according to inclusion/exclusion criteria. The sociodemographic factors assessed were age, sex, race/ethnicity, socioeconomic status, and geographic location. Outcomes were diagnosis, access to treatment, and patient outcomes. Of 84 articles included, 48 were US-based. Worldwide, increasing age and low socioeconomic status were associated with worse patient outcomes. In the US, men typically had worse outcomes than women, although women had poorer access to treatment, as did Black, Asian, and Hispanic patients. No consistent disparities due to sex were seen outside the US, and for most factors and outcomes, no consistent disparities could be identified globally. Too few studies examined disparities in diagnosis to draw firm conclusions. This first systematic analysis of health disparities in patients with MM identified specific populations affected, highlighting a need for additional research focused on assessing patterns, trends, and underlying drivers of disparities in MM.


Supplementary Table 6. Socioeconomic status and disparities in access to treatment in US and non-US studies
Author, year Outcome Summary of findings US studies Chamoun, 2021 [14] Receipt of HSCT In those aged <65 y, 33% of those with private insurance received HSCT vs 20% of those on Medicare (p < 0.0001  [81] Receipt of ASCT Education beyond high school not significantly associated with receipt of ASCT Non-US studies Chan, 2020 [15] OS following funding of bortezomib The most deprived groups (deciles 9/10) had an inferior 3-y OS vs other groups (0.57 vs 0.63; p = 0.026), and experienced no improvement in survival following the funding of bortezomib Uptake of 1L bortezomib, mean cumulative dosage The most deprived groups (deciles 9/10) had a similar uptake of 1L bortezomib vs other groups (p = 0.57), and mean cumulative dosage (

Access to ASCT
For those aged <65 y, access is high (98.2%). ASCT is fully reimbursed in all private and public health institutions. As reported by physicians, time to transplantation is considerably delayed in the public system Tarin-Arzaga, 2018 [74] Median number of treatment regimens Median number of treatment regimens lower for public (3) vs private (5) cohorts. ~70% of those in the private cohort receive further treatment lines with bortezomib (13%), carfilzomib (20%), lenalidomide (32%), or pomalidomide (5%). Those in the public cohort received thalidomide-based regimens exclusively Vargas-Serafin, 2021 [78] Induction therapy Low income not significantly associated with a decreased likelihood of undergoing induction therapy (OR 3.13, 95% CI 0.72-13.69; p = 0.111) Xu, 2020 [82] Received transplantation Those with high education levels more likely to receive transplantation vs those with low education levels (59.3% vs 27.9%; p < 0.001) Received regular treatment Those with high education levels more likely to undergo regular treatment vs those with low education levels (87.6% vs 60.7%, p < 0.001) For details on study population(s), data source(s), data period(s), sample size(s) analyzed, and country for non-US studies, see Supplementary Table 2. 1L, first-line; aOR, adjusted odds ratio; ASCT, autologous stem cell transplantation; CI, confidence interval; coeff, coefficient; EBRT, external-beam radiotherapy; Exp, exponential; HSCT, hematopoietic stem cell transplantation; MFRT, multiple-fraction radiotherapy; NHW, non-Hispanic Whites; NS, not significant; OR, odds ratio; OS, overall survival; SCT, stem cell transplant; SFRT, single-fraction radiotherapy; y, year; ZIP, Zone Improvement Plan. RSR A statistically significant decrease in relative survival was reported in older patients Jones, 2021 [39] Net survival For patients diagnosed after 2010, 1-, 5-, and 10-y survival was numerically greater for age <65 vs 65-74 y or 75-90 y Jurczyszyn, 2016 [40] OS Patients aged 21-40 y have a better OS than their counterparts aged 41-60 y, but the survival advantage observed in younger patients was lost in more advanced stages of MM Kim, 2014 [43] OS mOS was longer in patients aged <65 y vs those aged ≥65 y (55 vs 37 mo, p < 0.001) Manyega, 2021 [50] OS In univariate analysis, age at diagnosis was not significantly associated with length of survival Pulte, 2015 [60] 10-y age-standardized RSR 10-y age-standardized RSR decreased with increasing age and was lowest for the oldest age group assessed (65-74 y) Quaresma, 2015 [62] Age-adjusted net survival Net survival was generally lower for the oldest (75-99 y) vs the youngest (15-44 y) patients Radocha, 2019 [63] OS Age above 75 y represents an independent prognostic factor for survival Riva, 2019 [64] OS At a median follow-up of 32 mo, OS was 61.8% (median not reached) in patients aged ≤70 y vs 32 mo (95% CI 22.07-41.93) in patients aged >70 y (p < 0.001) Samy, 2015 [68] RSR Relative survival at 1, 3, and 5 y decreased with increasing age Tarín-Arzaga, 2018 [74] OS In multivariate analysis, age was not associated with OS Vargas-Serafin, 2021 [78] OS Age ≥65 y was significantly associated with decreased OS (40 mo vs 49 mo for ages <65 y; p = 0.041) For details on study population(s), data source(s), data period(s), sample size(s) analyzed, and country for non-US studies, see Supplementary Table 2. aHR, adjusted hazard ratio; aOR, adjusted odds ratio; CI, confidence interval; Dx, Diagnosis; HR, hazard ratio; MM, multiple myeloma; mo, months; mOS, median overall survival; MSS, myeloma-specific survival; NHB, non-Hispanic Black; NHW, non-Hispanic White; NS, not significant; OS, overall survival; PFS, progression-free survival; RR, risk ratio; RSR, relative survival rates; SEER, Surveillance, Epidemiology, and End Result; US, United States; vs, versus; WUSM, Washington University School of Medicine; y, year.

Supplementary Table 9. Age and disparities in mortality in US and non-US studies
Author Pastor-Barriuso, 2014 [55] Mortality rate Mortality increased with age but showed a gradual deceleration at older ages Riva, 2019 [64] Mortality rate Mortality rate was higher in older patients: 32.9% in those aged <70 y vs 56.6% in those aged >70 y (p = NR) Rosso, 2012 [66] ASMR for MM Death rate from MM was lower for women vs men, and the sex disparity increased with age. Death rate increased with age for both sexes For details on study population(s), data source(s), data period(s), sample size(s) analyzed, and country for non-US studies, see Supplementary Table 2. aOR, adjusted odds ratio; d, day; ASMR, age-standardized mortality rate; CI, confidence interval; EHR, excess hazard ratio; EMRR, excess mortality rate ratio; MM, multiple myeloma; NR, not reported; NS, not significant; OR, odds ratio; Q, quartile; y, year.

Supplementary Table 10. Sex and disparities in survival in US and non-US studies
Author 5-and 10-y RSR Notable gains in 5-and 10-y RSR for those aged <65 y for all race/ethnicity groups. For those aged 65-74 y, gains in 10-y RSR were significant for NHW and Hispanic patients, but not for NHB patients. For those aged ≥75 y, gains in 5-y RSR were seen for all race/ethnicity groups, whereas improvements in 10-y RSR were not observed for any stratum. Improvements in survival by sex and race/ethnicity strata indicate gains in 5-and 10-y RSR for both sexes and all race/ethnicity groups. Improvements in 5-y RSR were similar in NHW (29.1-50.0%; p < 0.001), NHB (32.0-50.1%; p < 0.001) and Hispanic patients (29.9-47.3%; p < 0.001). Improvements in 10-y RSR were also similar in NHW (13.  [15] OS No contribution of ethnicity to survival; mOS was inferior for Maori/Pasifika patients aged ≤70 y but similar for those aged >70 y Intzes, 2020 [36] OS No significant differences in OS by ethnic origin for Greek, Greek Muslim, and Balkan populations Samy, 2015 [68] Relative survival Controlling for age and sex, deprivation, comorbidity, and year of diagnosis, risk of death was significantly lower for Black vs White patients at 1 y and 3 y, and for South Asian vs White patients at 1 y, 3 y, and 5 y Sneyd, 2019 [72] Observed myeloma survival Maori ethnicity was significantly associated with increased hazard for death vs non-Maori ethnicity (HR 1.36; p < 0.001 adjusted for age at diagnosis, sex, and year of diagnosis) For details on study population(s), data source(s), data period(s), and sample size(s) analyzed, and country for non-US studies, see Supplementary Table 2. aHR, adjusted hazard ratio; aOR, adjusted odds ratio; CI, confidence interval; HR, hazard ratio; HW, Hispanic White; mOS, median overall survival; MSS, myeloma-specific survival; mMSS, median myelomaspecific survival; NHB, non-Hispanic Black; NHW, non-Hispanic White; NR, not reported; NS, not significant; OS, overall survival; PFS, progression-free survival; RSR, relative survival rates; vs, versus; y, year.  [73] OS Patients in the low-poverty group had a lower risk of death vs those in the medium/high poverty group (HR 0.879, 95% CI 0.840-0.920; p < 0.001) Non-US studies Afshar, 2020 [1] Net survival Numerical trend toward decreased net survival in more socioeconomically disadvantaged patients (Q2-Q5) vs less disadvantaged (Q1) Chan, 2020 [15] OS Socioeconomic deprivation was a negative prognostic factor for OS (HR 1.10, 95% CI 1.04-1.16) Harwood, 2020 [32] RSR A statistically significant decrease in RSR was reported in those of disadvantaged socioeconomic status vs affluent, but not for middle class vs affluent OS Patients with disadvantaged socioeconomic status had worse 5-y OS vs those of affluent status (33%, 95% CI 31-36 vs 39%, 95% CI 36-42; p = 0.002) Intzes, 2020 [36] OS Low socioeconomic status was associated with worse OS vs high status (HR 2.092, 95% CI 1.36-3.2; p = 0.01) Samy, 2015 [68] RSR RSR was numerically greater in more affluent patients at 1, 3, and 5 y Smailyte, 2016 [71] 5-y RSR 5-y RSR in men and women was highest for those in higher education (men: 20% difference between lower than secondary education vs higher; women: 15% difference between lower than secondary education vs higher). 5-y RSR was numerically higher in men vs women with higher education, but similar for those with secondary and lower than secondary education Tarin-Arzaga, 2018 [74] OS Those who were uninsured had a significantly higher risk of death vs private insurance.  Table 2. aHR, adjusted hazard ratio; aOR, adjusted odds ratio; CI, confidence interval; HR, hazard ratio; mo, month; mOS, median overall survival; mPFS, median progression-free survival; NCDB, National Cancer Database; NS, not significant; OS, overall survival; Q, quartile; RR, risk ratio; SEER, Surveillance, Epidemiology and End Result Program; USD, United States dollars; vs, versus; WUSM, Washington University School of Medicine; y, year; ZIP, Zone Improvement Plan.

Supplementary Table 17. Geography and disparities in mortality in non-US studies
Author, year Outcome Summary of findings Afshar, 2020 [1] 5-y EMRR There was a significant trend for increased mortality per quintile increase in socioeconomic disadvantage for urban and rural cases combined, but not significant for urban only Chen, 2016 [17] Inpatient mortality Inpatient mortality risk was significantly higher in urbanized areas vs less urbanized areas Liu, 2019 [47] ASMR Higher mortality rates were clustered in the more developed provinces (highest: Hong Kong Special Administrative Region, Zhejiang, and Shanghai; lowest: Hainan, Fujian, and Shandong) Mian, 2021 [52] Early mortality (vs no mortality) among patients receiving novel treatment No significant association between urban vs rural location and mortality in either younger or older patients